There are a large number of applications where knowledge of the 3D profile of an object is relevant. Different techniques exist for scanning the profile of an object. Basically they can be subdivided into radar based systems, ultrasound based systems and optical sensing systems.
Radar based systems have the advantage that they can sense a long range but have the disadvantage that they have a poor angular and depth resolution with regard to certain applications (e.g. for tracking the profile in a road).
Ultrasound based systems can be useful for short range sensing but their narrow bandwidth limits the depth sensitivity and the sampling resolution and the strong absorption in air limits the range to a few meter.
Optical sensing based methods can be subdivided in different types measuring the distance through time of flight measurements or by triangulation.
In time of flight methods the object is illuminated by a light source. From the delay between the emission and the detection the distance travelled by the light can be determined. The time of flight methods can make use of pulsed illumination.
In triangulation based systems, the unknown position of an object is calculated using trigonometry. An example of such a system is the Kinect system of Microsoft described in U.S. Pat. No. 8,320,621. In this system structured infra-red light (e.g. circles) is projected and viewed with a 3D camera. This system, which is primarily intended for indoor gaming and entertainment applications, is not suitable for outdoor use, due to the intensity of the sunlight.
In stereovision the distance to an object is determined from the local shift between corresponding parts in the images obtained by two cameras under different viewing angles or by one stereo camera with two lenses. Stereovision based systems can make use of existing set-ups and algorithms from robot vision, can operate using ambient illumination, and do not require projection. On the other hand stereovision based systems have the disadvantage that calibrated cameras with sufficient distance are required. Furthermore, sufficient structure in the images is required to enable cross correlation for parallax, it is difficult to detect flat surfaces and water, a sufficient number of pixels is required, the depth sensitivity is limited, and the cameras used should have a large dynamic range to cope with various light conditions. The biggest hurdle seems to be that stereovision based systems cannot work if there is insufficient structure in the object being scanned.
Therefore there is still room for improvement of surround sensing scan systems that can be used in outdoor situations scanning the profile of objects over a large range with a high resolution and with a high speed.